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Basic Question 2 of 3
Multicollinearity in linear regression is caused by:
II. The dependent variable and an independent variable being highly correlated with each other.
III. Two or more dependent variables being highly correlated with each other.
IV. Two or more independent variables being highly correlated with each other.
I. Heteroskedastic and serially correlated residuals.
II. The dependent variable and an independent variable being highly correlated with each other.
III. Two or more dependent variables being highly correlated with each other.
IV. Two or more independent variables being highly correlated with each other.
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Learning Outcome Statements
explain multicollinearity and how it affects regression analysis.
CFA® 2025 Level II Curriculum, Volume 1, Module 3.